Deep Dive: Globalisation and Growing Economies

Compiled 2026-09-28. Grounded in research/veridian/WBS14-verified-facts.md (Table of Contents; "Paper mechanics"; the §4.3.1 item-1 and item-2 narrative entries; the "globalisation-and-growing-economies.ts (spec 4.3.1 items 1-2) — audited 2026-09-13" log entry in full, including its four verbatim-bullet transcriptions for June 2022 Q1(a)-(d) and its two October 2021 Q1(b)/(c) re-verifications; the 2026-09-14 reconciliation entry for the same lesson; and the Flagged Issues / "Topics with enough verified material" sections) — every citation below was checked against that file's own sourcing, not re-derived from memory. Cross-read before writing, to keep this document additive rather than a restatement: the live lesson content/veridian/curriculum/wbs14/globalisation-and-growing-economies.ts (its spectrum/structural- transformation teach blocks, the GDP-per-capita worked chain, the specialisation/minimum-efficient- scale diagram, the FDI chain-drill, both level-exemplars and the full trap-taxonomy are NOT reproduced here), codex-definitions-and-application-bank.md and forge-exam-technique-guide.md in this same folder, signal-frequency-and-boundaries.md's frequency rows for 4.3.1.1/4.3.1.2, and content/veridian/question-bank/wbs14.ts (checked directly — no entry for this spec point exists there to duplicate). No new primary source was fetched for this document; it synthesises citations the facts bank already carries into a shape none of the existing documents provide, and surfaces one internal inconsistency in the facts bank's own sourcing that none of them had flagged.

#WBS14 CODEX Deep-Dive — Globalisation and Growing Economies (spec 4.3.1.1–4.3.1.2)

#What this document is, and isn't

The lesson file already teaches the developed/developing/emerging spectrum, derives why specialisation lowers a business's own average cost via minimum efficient scale, and works through the Apple/South Korea/Vietnam FDI case as a five-stage chain-drill. The CODEX definitions bank already carries a one-paragraph glossary entry and a short application paragraph for each sub-point. Neither document lays out, citation by citation, every real exam question this spec point has actually produced, with each citation's own indicative content set out in full and its confidence level stated explicitly — nor do they flag the one place where the facts bank's own sourcing disagrees with itself about what a real question actually tested. That is what this document adds. It does not re-teach the spectrum model, the fixed-cost/specialisation diagram or either level-exemplar — all three are cross-referenced, not restated.

Scope discipline carried over from the facts bank itself: 5 of the roughly 15 series held since first assessment (June 2020) were read in full (October 2021, June 2022, January 2023, October 2023, January 2024), plus one further series added later as a single targeted question-only pull (January 2026, and only Section A's Q1(a)-(e) sequence was even skimmed for structure — only Q1(d) was independently fact-checked). Every "confirmed" claim below traces to one of those pulls specifically, not to the full ~15-series population. Where the facts bank flags a citation as lower-confidence, that flag is repeated here rather than silently dropped.

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#Part 1 — Growing economies (spec 4.3.1.1): theory, real sub-cases, and micro-examples

#(a)–(b) The developed/developing/emerging spectrum, and Asia/Africa's growing economic power

The mechanism. Three dimensions move together as a single growth process, not three independent boxes: income (GDP per capita), productive structure (the share of output and employment still in low-productivity primary-sector activity versus higher-productivity secondary/tertiary activity), and institutional development (whether credit, contract enforcement and regulation function well enough for large-scale, complex transactions). "Emerging" names a country actively moving through that transition, not a fixed fourth label.

Real sub-case 1 — manufacturing-led growth (Vietnam). Vietnam's manufacturing sector drew large, multi-country FDI inflows, credited in a real mark scheme as raising productive capacity, lowering unemployment and improving the balance of payments via exports (October 2021 Q1c) — see Part 1's FDI entry below for the full citation. The same country is the real case for the employment-patterns sectoral-shift question (June 2022 Q1c, below): a workforce shifting from agriculture toward manufacturing and services as the economy grows.

Real sub-case 2 — resource-led growth (Senegal). Senegal is the facts bank's real African case, with gas and oil reserves named as the verified driver of a recent FDI surge into the country (cited in the context of a separate, 4.3.2.3 political-stability question — Senegal versus unstable neighbours Guinea and Mali). Senegal is also the real country used for a second GDP-per-capita Calculate opener (Jan 2023 Q1a, see below). Two real countries, two genuinely different growth drivers — a manufacturing/FDI story and a resource-extraction/FDI story — confirm that regional growth is not one mechanism repeated everywhere; a strong answer names which driver applies to the specific case in front of it.

Real sub-case 3 — the competitive-threat consequence. A real mark scheme (June 2022 Q1d, see below) names the consequence of this growth that a purely optimistic account misses: as developing economies grow, their own firms become genuine global competitors, not just smaller domestic also-rans. Chinese firms Haier and Lenovo, and Indian firms Tata and Infosys, are named directly as being among the world's biggest and fully capable of competing with European businesses globally, and developing economies' combined share of global exports of goods and services is stated as having reached 44.3% by 2019 — a real, dated figure, not an estimate constructed for this document.

Micro-example (real facts only, no invented figures). A two-sentence, fully-sourced Assess fragment: Vietnam's FDI-driven manufacturing growth lowered its own unemployment and improved its balance of payments (Oct 2021 Q1c); but the same growth process, seen from a European exporter's side, also grows genuine rivals — Haier, Lenovo, Tata and Infosys among them, backed by developing economies' 44.3% share of global exports by 2019 (June 2022 Q1d). Both facts are real, from two different mark schemes, about two different sides of the same regional growth story.

#(c) Indicators of growth — GDP, GDP per capita, HDI

The mechanism. GDP measures total output; it says nothing about how many people that output has to support. GDP per capita (GDP ÷ population) fixes that by dividing by population — the actual indicator this paper tests numerically. Its percentage change is not the percentage change in GDP minus the percentage change in population; population growth compounds in the denominator, so the two growth factors must be divided, not the two rates subtracted, for an exact figure. HDI adds two further dimensions (health, education) to income, combined via a geometric mean specifically so a very low score on one dimension can't be masked by strength in the other two.

Real sub-case — the exact real numbers behind the paper's most tested single calculation. June 2022 Q1(a) asked candidates to calculate Thailand's GDP per capita to two decimal places (4 marks): the mark scheme's own data is GDP $546bn and population 69,410,000; the mark scheme's own answer is $7,866.30. The mark split is K1 (stating GDP ÷ population) / App2 (one mark each for the two correct data points) / An1 (the computed answer) — and the mark scheme's own NB rule states a fully correct $7,866.30 earns 4/4, while the same number without the currency sign earns 3/4. The examiners' report confirms candidates who knew the correct formula generally did well; the two recorded slips were a missing currency sign and mishandled decimal places.

Second real sub-case — a second country, same question type. January 2023 Q1(a) is a second, independently confirmed GDP-per-capita Calculate opener, using Senegal as the case and QS2 (percentages) as its tagged quantitative-skill code. Genuinely thin beyond that: the facts bank confirms the question type and country but does not transcribe Senegal's own GDP/population figures or a mark-scheme answer anywhere — treat the Senegal GDP-per-capita opener itself (Jan 2023 Q1a) as confirmed, and any specific number attached to it as unverified until the primary PDF is re-checked.

A genuine open inconsistency, flagged rather than resolved. The facts bank contains three separate mentions stating Thailand was also the case for an Oct 2021 Q1(a) GDP-per-capita opener (the §4.3.1.1 narrative entry, the CODEX application bank's Part 2, and the FORGE guide's command-word table, which states that Oct 2021 and Jan 2023 both set a Calculate/GDP-per-capita opener). But the facts bank's own Paper-mechanics section separately tags that same Oct 2021 Q1(a) as a QS3 supply-and-demand diagram construction, not a GDP-per-capita calculation — and the one pass that directly re-fetched and re-extracted the real Oct 2021 mark scheme PDF only re-verified Q1(b) and Q1(c) of that series, explicitly leaving Q1(a) unchecked. Three mentions against one, and the one outlier plausibly confuses Oct 2021 with Jan 2024 (which the same FORGE table confirms really does open with a Construct/S&D-diagram question) — but this document treats what Oct 2021 Q1(a) actually tested as unverified pending a direct re-check of that specific PDF page, not as settled by majority count. This is the one place in this topic's sourcing that needs a primary-source re-fetch before it is taught as confirmed either way.

HDI — named but not numerically examined on this paper. Spec 4.3.1.1d names HDI alongside GDP and GDP per capita as an indicator of growth. No mark-scheme question in any of the six pulls checked asks a candidate to compute or interpret an HDI score on this specific paper — its full numeric derivation (the three dimension indices, the geometric-mean combination) is genuinely taught in the WEC14 economics lesson this paper's own content cross-references, not duplicated in a WBS14 mark scheme. Treat HDI on this paper as named vocabulary a candidate should recognise, not as tested calculation content.

#(c), continued — Employment patterns and trade opportunities

The mechanism. "Employment patterns" (4.3.1.1c) means which sector people work in as an economy grows — the shift from primary toward secondary/tertiary activity — not the total number of people in work. "Trade opportunities" for growth's implications must be answered for the specific party a question names (a country's own businesses, or a named group of foreign businesses), not for "the economy" generally — spec 4.1's own instruction that 4.3.1/4.3.2 content be understood in relation to businesses specifically.

Real sub-case — the employment-patterns question in full. June 2022 Q1(c) asked candidates to discuss the extent to which economic growth in a country such as Vietnam may have caused its employment patterns to change (8 marks, the paper's own confirmed three-band Discuss descriptor: L1 1-2 / L2 3-5 / L3 6-8). The real indicative content, in full, has ten linked points: economic growth is a rise in GDP; employment patterns means the sectoral distribution of the workforce; prior to 2000, Vietnam was an emerging economy with many people employed in the primary sector — a piece of real, verified scene-setting context the current lesson doesn't reproduce anywhere; since 2000, Vietnam's GDP more than doubled between 2010 and 2020, indicating rising incomes and industrialisation; employment likely moved from primary toward manufacturing; Vietnam's exports of goods and services tripled over the same period, indicating a rising tertiary sector too; but whether growth itself caused the shift is uncertain, because many countries invest (FDI) in economies like Vietnam specifically for cheap labour — meaning the FDI inflow, not growth in the abstract, may be the real shared driver of both the sectoral shift and the GDP growth. The examiners' report is direct: most candidates wrote about employment totals rather than the sectoral shift, and even good answers often skipped the required balance/assessment step.

Real sub-case — the trade-opportunities question, its under-used specificity. June 2022 Q1(d) asked candidates to assess how economic growth in developing economies may affect the trade opportunities for European businesses (12 marks, this paper's confirmed four-band Assess descriptor: L1 1-2 / L2 3-4 / L3 5-8 / L4 9-12). Thirteen real indicative-content points sit behind it, and two clusters go beyond a generic larger-market/cheaper-inputs answer: developing economies don't just want consumer goods as they grow — the mark scheme names services specifically: infrastructure, engineering, transport and communications as real, separately-creditable demand categories a growing economy needs from abroad; and European businesses can use this growth to extend an existing product's life cycle by launching it into a market where it is still novel, rather than only developing something new. Both points are real, confirmed indicative content for this exact question, taught in the current lesson only in general terms (cheaper inputs and production capacity) rather than with this level of named specificity. The balancing content — Haier/Lenovo/Tata/Infosys, the 44.3% export-share figure, and the innovate/quality/brand-led-vs-price-only differentiator — is covered in Part 1's growing-power sub-case above and is not repeated twice.

Real secondary anchor — Australia as a developed economy. October 2021 Q1(b) asked candidates to explain one characteristic of a developed economy (4 marks). The mark scheme's own model answer names Australia's reliance on the tertiary sector, backed by two real figures: services comprise 62.7% of Australia's GDP and employ 78.8% of its labour force. Other real developed-economy comparators the mark scheme names directly: the US, UK, New Zealand and Germany.

Micro-example, the under-used content specifically. A single sentence uses the two newly-surfaced Q1(d) bullets without reproducing the lesson's own Northgate Apparel case: a UK engineering-services firm gains a genuinely different trade opportunity from a developing economy's growth than a UK consumer-goods exporter does — the engineering firm sells the infrastructure a growing economy needs built, while the consumer-goods firm sells a product whose UK life cycle has already matured into decline, restarted by a market where it is still new.

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#Part 2 — International trade and business growth (spec 4.3.1.2): theory, real sub-cases, and micro-examples

#(a)–(b) Exports, imports, and specialisation

The mechanism. Exports are goods/services sold abroad by domestic residents; imports are goods/ services bought from abroad. Specialisation is a country or business concentrating production on what it can produce most efficiently, trading for the rest — raising output and efficiency, but concentrating risk in whichever single market or commodity has been specialised into.

Real sub-case — Thailand's rubber exports, both credited mechanisms. June 2022 Q1(b) asked candidates to explain one advantage for Thailand of specialising in the production of rubber (4 marks, K1/App2/An1). The mark scheme's own model answer develops the advantage through jobs and employment, not cost: Thailand is the world's biggest exporter of natural rubber, with 42.4% of that output sold to China, and this scale of demand needs many workers to keep up with supply — creating jobs and incomes. The mark scheme separately allows any other appropriate response, which is understood to credit a cost-based route (spreading fixed costs over a larger export market, cutting average cost toward minimum efficient scale) — the mechanism the current lesson's own diagram derives in full, not repeated here. The examiners' report is specific about where marks were actually lost: most candidates correctly named a relevant advantage, but the analysis often didn't develop far enough to explain why the identified advantage actually came about — a naming-without-developing failure, not a wrong-answer one.

Micro-example (real numbers, no invented data). One real fact carries the whole mark scheme's own worked answer: 42.4% of Thailand's rubber output goes to China. That single figure is the entire App evidence needed to develop the jobs/income mechanism into a full 4-mark answer — name the advantage (specialisation → export demand), apply the figure (42.4% to China, a growing economy), and explain why (that scale of demand needs workers to keep up with supply, creating jobs and incomes).

#(c) Foreign direct investment and its link to business growth

The mechanism. FDI is investment by a firm or individual from one country into productive assets in another — read from two sides at once: a growth mechanism for the investing business (new capacity, a new market foothold) and a growth driver for the recipient economy. This spec point (4.3.1.2c) and spec 4.3.1.3(e), increased investment flows, share almost all of their real exam evidence, because they are the same transaction examined from two different angles — a distinction this document keeps explicit rather than silently merging, matching the same discipline the companion 4.3.1.3 deep-dive uses for the identical citation.

Real sub-case — the Vietnam/South Korea/Apple case, in full. October 2021 Q1(c) asked candidates to discuss the possible impact of increased FDI flows on the national economy of a country such as Vietnam (8 marks, three-band Discuss). Nine real indicative-content points: FDI means capital invested in Vietnam's productive capacity; it increased every year for ten years; South Korea invested $7.9bn, and Apple moved AirPods production there; this creates jobs, lowering unemployment; rising incomes raise GDP; the balance of payments improves as manufactured exports (like AirPods) rise; tax revenues rise, funding government spending; but if growth is too rapid, inflation can result; and FDI can cause negative impacts such as environmental damage. Every one of these nine points is already taught in the current lesson's chain-drill and reference-card — nothing new surfaces here, so it is stated compactly rather than re-derived.

Micro-example (real, compact, from the investing-firm side). Apple's own decision — moving AirPods assembly to Vietnam rather than relying solely on its existing supply chain — is itself the real, confirmed evidence for FDI as a growth mechanism for the investing business: new production capacity, reduced single-country concentration. That one sentence, sourced to the same Oct 2021 Q1(c) mark scheme, is the investing-side half of a transaction the lesson's chain-drill already develops fully from the recipient-economy side; it is not restated here.

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#Part 3 — Complete real exam-citation inventory for spec 4.3.1.1–4.3.1.2

Every row is a real mark-scheme or examiners'-report citation the facts bank carries for this topic specifically. Nothing below is invented or estimated.

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#Part 4 — Cross-citation synthesis: what the evidence as a whole actually shows

Five things are visible only once every citation above is read together, rather than one at a time inside its own spec sub-point.

1. This topic supplies the paper's only confirmed 8-mark Discuss content across the whole WBS14 build. The current lesson's own header notes that, before the Vietnam employment-patterns question was added as a level-exemplar, all eight WBS14 lessons combined had zero worked examples for the 8-mark Discuss tariff — every level-exemplar elsewhere was built for the 12-mark Assess or 20-mark Evaluate instead, despite Discuss being a confirmed, paper-wide Section A component with its own distinct three-band structure. Two of this topic's own six core citations (June 2022 Q1c; October 2021 Q1c) are Discuss questions — this spec point is structurally this course's anchor for that command word, not an incidental example of it.
2. The 4-mark opener alternates between two genuinely different tasks, and this topic owns one of them. Across the papers sampled, Section A's Q1(a) is either a GDP-per-capita Calculate (this topic, spec 1d) or a supply-and-demand Construct (protectionism, spec 4.3.1.4b/e) — never both in the same series. A student should confirm which task a given paper's Q1(a) actually is before assuming the mode from a previous series' pattern, a discipline the FORGE guide already states generally and this topic's own citation table confirms concretely (Thailand and Senegal both real GDP-per-capita cases; the Oct 2021 Q1(a) contradiction flagged in Part 1 is precisely a case of this ambiguity surfacing inside the facts bank's own sourcing).
3. Every named growth case is Vietnam, Thailand, Senegal or Australia — no confirmed citation for this topic uses a European, North American or Latin American case. The same pattern the companion 4.3.1.3 deep-dive documents for that spec point holds here too. Worth naming as a pattern in the sample checked, not a rule about what Pearson would set next — this facts bank's own discipline against reading a sample pattern as a probability applies here exactly as it does elsewhere.
4. Two real, under-used indicative-content bullets are genuinely new to this course's own coverage of this topic, both surfaced by this document rather than by the earlier lesson audits: Vietnam's pre-2000 starting point as scene-setting context for the employment-patterns question (June 2022 Q1c), and the services/infrastructure/product-life-cycle specificity behind the trade-opportunities question (June 2022 Q1d). Neither changes what the lesson currently teaches at the level of mechanism — both were already correctly taught in general terms — but both are real, quotable specificity a strong answer could use that the lesson's own worked material doesn't currently supply.
5. Jobs/income and cost are two independently-creditable routes to the same specialisation advantage, confirmed by the same mark scheme. June 2022 Q1(b)'s own model answer develops Thailand's rubber advantage through jobs and export demand; its own allowance for any other appropriate response separately credits the cost/minimum-efficient-scale route the current lesson's diagram derives in full. A revision plan that treats these as competing explanations, rather than two real, independently creditable ones, is working from an incomplete picture of what the mark scheme itself rewards.

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#Sources checked for this document

research/veridian/WBS14-verified-facts.md — Table of Contents (spec 4.3.1.1/4.3.1.2 wording); "Paper mechanics" (command-word/mark/QS-code table, including the internally inconsistent Oct 2021 Q1(a) tagging); the main §4.3.1 item-1 and item-2 narrative entries; the "globalisation-and-growing-economies.ts (spec 4.3.1 items 1-2) — audited 2026-09-13" log entry in full, including its verbatim bullet transcriptions for June 2022 Q1(a)-(d) and October 2021 Q1(b)-(c); the 2026-09-14 reconciliation entry for the same lesson; and the "Topics with enough verified material" / "Flagged issues" sections (sample-size and third-party-mirror sourcing caveats, and the January 2026 targeted-pull scope note). content/veridian/curriculum/wbs14/globalisation-and-growing-economies.ts — read in full to confirm what is already taught, so nothing here duplicates its spectrum/structural-transformation teach blocks, its GDP-per-capita worked chain, its specialisation/minimum-efficient-scale diagram, its FDI chain-drill, either level-exemplar, or its trap-taxonomy. content/veridian/technique-hub/wbs14/codex-definitions-and-application-bank.md, forge-exam-technique-guide.md, signal-frequency-and-boundaries.md and codex-deep-dive-factors-driving-globalisation.md — read in full for the same non-duplication check, and to match this document's citation-inventory/confirmed-vs-not-confirmed/cross-citation-synthesis structure to the convention the last of these already established for the adjacent spec point. content/veridian/question-bank/wbs14.ts — checked directly; contains no entry for this spec point.